Comparison of hemispheric asymmetry measurements for emotional recordings from controls

Four asymmetry measurements (conventional coherence function (CCF), cross wavelet correlation (CWC), phase lag index (PLI), and mean phase coherence (MPC)) have been compared to each other for the first time in order to recognize emotional states (pleasant (P), neutral (N), unpleasant (UP)) from controls in EEG sub-bands (delta (0–4 Hz), theta (4–8 Hz), alpha (8–16 Hz), beta (16–32 Hz), gamma (32–64 Hz)) mediated by affective pictures from the International Affective Picture Archiving System (IAPS). Eight emotional features, computed as hemispheric asymmetry between eight electrode pairs (Fp1 − Fp2, F7 − F8, F3 − F4, C3 − C4, T7 − T8, P7 − P8, P3 − P4, and O1 − O2), have been classified by using data mining methods. Results show that inter-hemispheric emotional functions are mostly mediated by gamma. The best classification is provided by a neural network classifier, while the best features are provided by CWC in time-scale domain due to non-stationary nature of electroencephalographic (EEG) series. The highest asymmetry levels are provided by pleasant pictures at mostly anterio-frontal (F3 − F4) and central (C3 − C4) electrode pairs in gamma. Inter-hemispheric asymmetry levels are changed by each emotional state at all lobes. In conclusion, we can state the followings: (1) Nonlinear and wavelet transform-based methods are more suitable for characterization of EEG; (2) The highest difference in hemispheric asymmetry was observed among emotional states in gamma; (3) Cortical emotional functions are not region-specific, since all lobes are effected by emotional stimuli at different levels; and (4) Pleasant stimuli can strongly mediate the brain in comparison to unpleasant and neutral stimuli.

     

Right,left characteristic sequences and column,row minimal indices of a singular pencil

For a general singular pencil sF — G?? ^m×n [s] the right, left characteristic sequences _r(F, G), _l(F, G) are defined and they are shown to be of the piecewise arithmetic progression type. The sets of column, row minimal indices ?_c(F, G), ?_r(F, G) are defined by a singular points analysis of _r(F, G), ?_l(F, G) respectively. Thus, ?_c(F, G), ?_r(F, G) emerge as numerical invariants of the ordered pair (F, G) and they may be computed by rank tests on Toeplitz matrices defined on (F, G).     

Energy expenditure and clearing snow: a comparison of shovel and snow pusher

In order to assess the energy demands of manual clearing of snow, nine men did snow clearing work for 15 min with a shovel and a snow pusher. The depth of the snowcover was 400–600 mm representing a very heavy snowfall. Heart rate (HR), oxygen consumption ([Vdot]O₂), pulmonary ventilation ( [Vdot]O_E), respiratory exchange ratio (R), and rating of perceived exertion (RPE) were determined during the work tasks. HR, [Vdot]O_E, R, and RPE were not significantly different between the shovel and snow pusher. HR averaged (± SD) 141 ± 20bmin_-1 with the shovel, and 142 ± 19 beats-min_-1 with the snow pusher. [Vdot]O₂was 2·1 ± 0·41 min_-1 (63 ± 12% [Vdot]O₂max) in shovelling and 2·6 ± 0·51 min_-1 (75 ± 14% [Vdot]O₂max) in snow pushing (p< 0·001). In conclusion manual clearing of snow in conditions representing heavy snowfalls was found to be strenuous physical work, not suitable for persons with cardiac risk factors, but which may serve as a mode of physical training in healthy adults.     

Detection of mosaic virus disease in cassava plants by sunlight-induced fluorescence imaging: a pilot study for proximal sensing

Cassava mosaic disease (CMD) is a prominent virus infection that causes considerable crop damage and yield reduction. Early detection of crop damage by remote sensing could be a useful tool for initiating remedial measures to reduce further crop damage. This article presents a non-destructive method for detection and classification of CMD infection, based on the red:far-red chlorophyll (chl) fluorescence image ratio. This pilot study was carried out in 14 varieties of potted cassava plants (Manihot esculenta Crantz) with a multispectral imaging system (MSIS) consisting of an electron multiplying charge coupled device (EMCCD) camera. Sunlight-induced chl fluorescence (SICF) images of plant leaves were recorded using the MSIS at the Fraunhofer lines of O₂-B at 687 nm and O₂-A at 759.5 nm and their off-lines at 684 and 757.5 nm. The recorded images were analysed using the Fraunhofer line discrimination (FLD) technique to extract the SICF from the solar reflectance in the recorded images. The chl fluorescence image ratio (red:far-red, F₆₈₇:F₇₆₀) was computed and correlated with the laser-induced chl fluorescence (LICF) ratio (F₆₈₅:F₇₃₅) determined by point monitoring, chl content variation, and the net photosynthetic rate (P_n). The scatter plot of the F₆₈₇:F₇₆₀ image ratio showed good discrimination between different levels of CMD infection as evidenced by the high sensitivity and specificity values. It is observed that the fluorescence image ratio (F₆₈₇:F₇₆₀) has a good correlation with P_n (coefficient of determination (R²) = 0.85), chl content (R² = 0.82), and the LICF ratio (F₆₈₅:F₇₃₅) (R² = 0.80), thereby highlighting the potential of the SICF image ratio in the discrimination of CMD infection. The results clearly indicate that changes in the red:far-red fluorescence image ratio due to CMD stress can easily be detected at an early stage and the technique has great potential for monitoring the health of crops and vegetation from proximal sensing platforms.     

Estimation of spatially enhanced soil moisture combining remote sensing and artificial intelligence approaches

The main objective of this study is to combine remote-sensing and artificial intelligence (AI) approaches to estimate surface soil moisture (SM) at 100 m spatial and daily temporal resolution. The two main variables used in the Triangle method, that is, land-surface temperature (LST) and vegetation cover, were downscaled and calculated at 100 m spatial resolution. LSTs were downscaled applying the Wavelet-Artificial Intelligence Fusion Approach (WAIFA) on Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat imageries. Vegetation fractions were also estimated at 100 m spatial resolution using linear spectral un-mixing and Wavelet–AI models. Vegetation indices (VIs) were replaced with the vegetation fractions obtained from sub-pixel classification in the T_s–VI triangle space. The downscaled data were then used for calculating the evaporative fraction (EF), temperature-vegetation-dryness index (TVDI), vegetation temperature condition index (VTCI), and temperature-vegetation index (TVX) at 100 m spatial resolution. Thereafter, surface SM modelling was performed using a combination of Particle Swarm Optimization with Adaptive Neuro Fuzzy Inference System (PSO-ANFIS) and Support Vector Regression (PSO-SVR) modelling approaches. Results showed that the best input data set to estimate SM includes EF, TVDI, T_s, F_vegetation, F_soil, temperature (T), precipitation at time t (P_t, P_{t – 1}, P_{t – 2}), and irrigation (I). It was also confirmed that PSO-SVR outperformed the PSO-ANFIS modelling approach and could estimate SM with a coefficient of determination (R²) of 0.93 and a root mean square error (RMSE) of 1.29 at 100 spatial resolution. Range of error was limited between ?2.64% and 2.8%. It was also shown that the method proposed by Tang et al., (2010) improved the final SM estimations.     

Inclusion properties for random relations under the hypotheses of stochastic independence and non-interactivity

This paper investigates whether random set inclusion is preserved by non-interactivity and by stochastic independence. Let (𝒳₁, x ₁), (𝒳₂, x ₂) be two random sets on U ₁ and U ₂, respectively, and let (𝒴₁, y ₁), (𝒴₂, y ₂) be two consonant inclusions of theirs. Let (𝒵₁, z ₁) be the random relation on U ₁ × U ₂ obtained from (𝒳₁, x ₁) and (𝒳₂, x ₂) under the hypothesis of stochastic independence, and let (𝒵₂, z ₂) ((𝒵₃, z ₃), respectively) be the random relation on U ₁ × U ₂ obtained from (𝒴₁, y ₁), (𝒴₂, y ₂) under the hypothesis of non-interactivity (stochastic independence, respectively). We prove that these hypotheses do not imply that (𝒵₁, z ₁) ? (𝒵₂, z ₂), but imply that (𝒵₁, z ₁) ? (𝒵₃, z ₃).     

The influence of flywheel weight and pedalling frequency on the biomechanics and physiological responses to bicycle exercise†

The physiological, subjective and biomechanical effects of altering flywheel weight and pedalling rate on a Quinton Model 870 bicycle ergometer were studied. Steel plates were added to the flywheel to increase its weight to 35·9 kg with a moment of inertia of 1·65 kg m². A 1·5 kg spoked wheel with a moment of inertia of 0·1 kg m² was used as the light flywheel. Eight subjects pedalled on two separate occasions for 6 min at 40, 50, 60, 70, 80 and 90 r.p.m. with workload levels representing 30 and 60% of their [Vdot]O₂max with each flywheel. Force plate pedals were used to measure the total resultant force on the pedals (F_R ) and the component perpendicular to the crank arm (F_T). A force effectiveness index (FEI) was denned as the average of F_T/F_R over a crank cycle. The result showed no statistically significant change (p<0·05) in [Vdot]O₂, heart rate and rating of perceived exertion of the FEI as a function of flywheel weight except for the [Vdot]O₂ at 50 r.p.m. for the light workload. As the r.p.m. increased from 40 to 90 r.p.m., the FEI decreased from 0·5 to 0·35 with the heavy load and from 0·36 to 0·22 with the light load. Measured physiological, subjective and biomechanical indices did not change significantly with flywheel weight. Increasing the pedalling rate caused a significantly less effective application of forces to the crank arm with only a small change in [Vdot]O₂.     

DEPARTMENT OF SCIENTIFIC AND INDUSTRIAL RESEARCH: HUMAN SCIENCES COMMITTEE

Maximal power output during short term constant velocity cycling and vertical jumping from a force platform has been studied in five healthy young male subjects. From the measurements on the force platform the peak (instantaneous) power output (P), net impulse (I_N ), force (F₁ ). velocity of take-off(V_T ) and height of jump(h) were calculated. The corresponding values for power (H), force (F) and velocity (V) on the bicycle were obtained from analysis of the force-velocity relationship.

The results (mean ± S.D.) showed that on the force platform F₁ P, I_N, V_T and h were 1073± 167N, 2205±310W, 154±17Ns, 2·48+0·15ms^?1 and 31 +4cm. h was positively associated with both I_N (r= +0·77) and P (r = 0·67). The mean maximal power output for cycling was 854W(39%) greater than jumping and was achieved at a 271N (25%) increase in F and a reduction in V. Nevertheless they were closely related.

Platform P(W) = 717·6 + 0·483 bicycle H(W) r= +0·74

A comparison of linear and curvilinear (hyperbolic) analysis of the F/V bicycle data showed that the latter did not reduce the variance of observations and was not, therefore, statistically justifiable (Wilkie 1950). The mean intra-subject variations of P and H were 6·6%± 1·8 and 40%+1·2. The relative values of F and V at H were both found to be approximately 50% of their respective maximal values.

It was concluded that short term power output can be measured simply and accurately in man during the performance of two activities. Rotational movement of the legs as in cycling produces higher values of peak power output then vertically lifting body weight. For the achievement of peak power output in cycling, relative force and speed of movement must both correspond to approximately half of their respective maximal values.     

Two-step compensation of nonlinear systems

We study the problem of stabilization of nonlinear plants. We show that given a nonlinear plant P, if there exists a (nonlinear) compensator F, possibly unstable, which stabilizes P, then, with P₁: = P(I − F(− P))⁻¹, any C defined by C:= F + Q(I − P₁Q)⁻¹ for some finite-gain stable Q will stabilize P.     

Estimation of nitrogen,phosphorus, and potassium contents in the leaves of different plants using laboratory-based visible and near-infrared reflectance spectroscopy: comparison of partial least-square regression and support vector machine regression methods

Nitrogen, phosphorus, and potassium are some of the most important biochemical components of plant organic matter, and hence, estimation of their contents can help monitor the metabolism processes and health of plants. This study, conducted in the Yixing region of China, aimed to compare partial least squares regression (PLSR) and support vector machine regression (SVMR) methods for estimating the nitrogen (C _N), phosphorus (C _P), and potassium (C _K) contents present in leaves of diverse plants using laboratory-based visible and near-infrared (Vis-NIR) reflectance spectroscopy. A total of 95 leaf samples taken from rice, corn, sesame, soybean, tea, grass, shrub, and arbour plants were collected, and their C _N, C _P, C _K, and Vis-NIR reflectance data were measured in a laboratory. The PLSR and SVMR methods were calibrated to estimate the C _N, C _P, and C _K contents of the obtained samples from spectral reflectance. Cross-validation with an independent data set was employed to assess the performance of the calibrated models. The calibration results indicated that the PLSR method accounted for 59.1%, 50.9%, and 50.6% of the variation of C _N, C _P, and C _K, whereas the SVMR method accounted for more than 90% of the variation of C _N, C _P, and C _K. According to cross-validation, the SVMR method achieved better estimation accuracies, which had determination coefficients of 0.706, 0.722, and 0.704 for C _N, C _P, and C _K, respectively, than the PLSR method, which had determination coefficients of 0.663, 0.643, and 0.541. It was concluded that the SVMR method combined with laboratory-based Vis-NIR reflectance data has the potential to estimate the contents of biochemical components.     

Influence of tyre pressure and vertical load on coefficient of rolling resistance and simulated cycling performance

The coefficient of rolling resistance (C _r) for pneumatic tyres is dependent on hysteresis loss from tyre deformation which is affected by the vertical force applied to the tyres (F _v) and the tyre inflation pressure (P _r). The purpose of this paper was to determine the relative influence of five different levels of P _r and four different levels of F _v on C _r and to examine the relationships of C _r with P _r and F _v during cycling locomotion. F _v was modified through carriage of additional mass by the subject. C _r was determined with the coasting deceleration method from measurements performed in a level hallway. Iterations minimizing the sum of the squared difference between the actual deceleration distance and a predicted deceleration distance were used to determine C _r. This latter distance was computed from a derivation based on Newton's second law applied to the forces opposing motion. C _r was described by a hyperbolic function of P _r (C _r = 0.1071 P _r ^?0.477, r ² = 0.99, p &lt; 0.05), decreasing 62.4% from 150 kPa (C_r= 0.0101) to 1200 kPa (C_r = 0.0038). F _v was related to C _r by a polynomial function (C _r = 1.92.10^?8 F _v ² ?2.86.10^?5 F _v + 0.0142, r ² = 0.99, p = 0.084), with an added mass of 15 kg (C _r = 0.0040) resulting in an 11.4% increase in C _r compared with no added mass (C _r = 0.0035). From this study, it is concluded that the relationships of P _r and F _v with C _r for cycling are non-linear. Furthermore, a simulation model shows that changes in P _r and F _v of the magnitude examined here have an important effect on competitive cycling performance.     

The effect of glycogen depletion on the curvature constant parameter of the power-duration curve for cycle ergometry

For high-intensity cycle ergometer exercise, the relation between power (P) and its tolerable duration (t) has been well characterized by the hyperbolic relationship: (P-θ_F)t = W', or P = W'(1/t)+θ_F, where θ_F may be termed the ‘fatigue threshold’. The curvature constant (W') reflects a constant amount of work which is postulated to be equivalent to a finite energy store that relates to the oxygen-deficit: phosphagen pool, anaerobic glycolysis and oxygen stores. Compared to theta_F, the physiological nature of W' has received little consideration. The purpose of this study was therefore to establish the parameters of the power-duration curve (θ_F and W') for subjects in normal glycogen (NG) and glycogen depleted (GD) states. Seven healthy male subjects (aged 22 to 41 years) each performed four high-intensity square-wave exercise bouts on an electrically braked cycle ergometer under two different muscular glycogen content conditions, i.e. NG and GD states. Subjects performed the following exercise on the evening before the trial day to induce the GD state. Initially, they performed a 75-min cycling exercise at 60% of VO₂max. After a 5-min rest period, they subsequently repeated a 1-min cycling bout at 115% of VO₂max (separated by 1-min rest periods) until the subject could no longer maintain the prescribed pedal rate for the full minute. Subjects then reported to the laboratory after an overnight fast and performed a single high-intensity exercise bout. The GD procedure was repeated four times at 1-week intervals. In the GD state, the respiratory exchange ratio (RER) (VO₂/VCO₂) value during a recumbent control period prior to the trial was significantly lower than that in the NG state [GD: 0.84±0.02, NG: 0.94±0.04, mean±SD]. There was no significant difference for θ_F between GD and NG state [NG: 197.1±31.9 W, GD: 190.6±28.2 W]. W' in contrast was significantly reduced by the GD procedure [NG: 12.83±2.21 kJ, GD: 10.33±2.41 kJ]. The present results indicate that the muscular glycogen store seems to be an important determinant of the curvature constant (W') of the power-duration curve for cycle ergometry.     

Dynamics of the relationship between NDVI and SWIR32 vegetation indices in southern Africa: implications for retrieval of fractional cover from MODIS data

Fractional cover of photosynthetic vegetation (F_PV), non-photosynthetic vegetation (F_NPV), and bare soil (F_BS) has been retrieved for Australian tropical savannah based on linear unmixing of the two-dimensional response envelope of the normalized difference vegetation index (NDVI) and short wave infrared ratio (SWIR)32 vegetation indices (VI) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data. The approach assumes that cover fractions are made up of a simple mixture of green leaves, senescent leaves, and bare soil. In this study, we examine retrieval of fractional cover using this approach for a study area in southern Africa with a more complex vegetation structure. Region-specific end-members were defined using Hyperion images from different locations and times of the season. These end-members were applied to a 10-year time series of MODIS-derived NDVI and SWIR32 (from 2002 to 2011) to unmix F_PV, F_NPV, and F_BS. Results of validation with classified high-resolution imagery indicated major bias in estimation of F_NPV and F_BS, with regression coefficients for predicted versus observed data substantially less than 1.0 and relatively large intercept values. Examination with Hyperion images of the inverse relationship between the MODIS-equivalent SWIR32 index and the Hyperion-derived cellulose absorption index (CAI) to which it nominally approximates revealed: (1) non-compliant positive regression coefficients for certain vegetation types; and (2) shifts in slope and intercept of compliant regression curves related to day of year and geographical location. The results suggest that the NDVI–SWIR32 response cannot be used to approximate the NDVI–CAI response in complex savannah systems like southern Africa that cannot be described as simple mixtures of green leaves, dry herbaceous material high in cellulose, and bare soil. Methods that use a complete set of multispectral channels at higher spatial resolution may be needed for accurate retrieval of fractional cover in Africa.     

Retrieving understorey dynamics in the Australian tropical savannah from time series decomposition and linear unmixing of MODIS data

Retrieval from remote sensing of separate temporal dynamics for the understorey layer in tropical savannahs would be beneficial for monitoring fuel loads, biomass for livestock, interrelationships between trees and grasses, and modelling of savannah systems. In this study, we combined unmixing of fractional cover with normalized difference vegetation index (NDVI) and the short wave infrared ratio (SWIR32) with time series decomposition of the NDVI to attempt to fully resolve the dynamics of the herbaceous understorey in the Australian tropical savannah based on the fractions of photosynthetic herbaceous vegetation (F_PVH) and non-photosynthetic vegetation (F_NPV), from the woody overstorey, represented by the fraction of photosynthetic vegetation in the tree canopy (F_PVW). Evaluation of F_PVH against field data gave moderate relationships between predicted and observed values (R² between 0.5 and 0.6); since semivariogram metrics of representativeness indicated that field sites were relatively unrepresentative of variation at the Moderate Resolution Imaging Spectroradiometer MODIS) pixel scale. Both F_PVW and F_PVH produced strong linear relationships (root mean square error < 0.1 units) with high-resolution Orbview 3 cover fractions classified from tasselled cap transformations. However, F_NPVH (non-photosynthetic herbaceous cover fraction) retrievals at southern arid locations produced an evaluation relationship with a greater deviation from the 1:1 line than for northern locations. This suggested that there may be limitations on the NDVI–SWIR32 unmixing approach in more sparsely vegetated savanna. Maps of average annual maximum F_PVH, F_NPVH, and total herbaceous cover fraction could be used as indicators of savannah productivity and landscape health. However, close examination of the limitations of the NDVI–SWIR32 response may be required for application of this method in other global savannahs.     

Regional remapping of the basement complex outcrops,using factor analysis to spectrometric data,of the Gabal Eteiqa,Eastern Desert,Egypt

Regional radiometric-geological mapping of the outcropping basement complex in the Gabal Eteiqa area has been carried out through the application of factor analysis technique

Three factor scores (F_?1 F_?2 and F_?3), which reflect the interrelation of the seven spectrometric variables (TC, eU, eTh, K, eU/eTh, eU/K and eTh/K), are sufficient to outline the different rock units, F_?1 outlines the highly-radioactive rocks such as granodiorites, granites, ring complexes and acidic volcanics. The granodiorite and ring complexes are completely differentiated by F_?2 scores. The F_?3 values enable the granitic plutons to be divided into numerous subunits (e.g. G₁" G₂, G₃ and G₄). It is believed that the low radiometric level of G₄ is due to the Quaternary wadi deposits that overlie the granites, an interpretation confirmed by aerial photomosaics.     

Metabolic and respiratory profile of the upper limit for prolonged exercise in man

For high-intensity cycling, power (P) can be well described as a hyperbolic function of tolerable work duration (t): P=(W'/t) + P _LL W' is a constant and P _LL is the lower limit (asymptote) for P which is shown to occur at an O₂ uptake ([Vdot]O₂) lying above the estimated threshold for sustained blood [lactate] increase (Θ_Iac) but below the maximum [Vdot]O₂ ([Vdot]O₂max) obtained during incremental cycling. This relation suggests that, above P _LL, only a certain amount of work (W') can be accomplished regardless of its rate of performance, with [Vdot]O₂ max being attained at fatigue. Hence, P _LL defines a point of discontinuity in the [Vdot]O₂-P relation for supra-Θ_Iac exercise. In order to determine the factors responsible for the continued increase in [Vdot]O₂ (to the maximum fatiguing value) at power outputs >P _LL, we documented the temporal profiles of metabolic (rectal temperature; blood [lactate], [pyruvate], [norepinephrine], [epinephrine]) and respiratory ([Vdot]_E; [Vdot]O₂; [Vdot]CO₂; blood pH, PCO₂, [HCO₃ ^?]) responses to constant-load cycling in eight healthy males at P _LL (24 min) and slightly above P _LL (to exhaustion, i.e. < 24 min). [Vdot]O₂ manifested a delayed steady state at P _LL, despite catecholamine levels and core temperature continuing to increase throughout; blood [lactate] and pH plateaued, however. In contrast, [Vdot]O₂ continued to increase slowly for the duration of the exercise > P _LL and attained [Vdot]O₂max. The response patterns at P _LL, and > P _LL suggest that the slow phase of the [Vdot]O₂ response is best correlated with the temporal profile of blood [lactate], and hence the site and route of metabolism of this variable may play a major role in the [Vdot]O₂ kinetics for high-intensity exercise.     

Seasonal and inter-annual variation in surface energy fluxes and forcing parameters in agro-climatic regions of India

Understanding changes in monsoon variability over a decade requires thorough knowledge of the seasonal and inter-annual variability in surface energy flux and its forcing parameters (land surface and meteorology) in response to climate change. In the present study, the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua climate model gridded global products (0.05° × 0.05° spatial resolution) of land surface temperature (LST; T_s), normalized difference vegetation index (NDVI), and surface albedo (α) were used to generate seasonal (June–September) and inter-annual (2003–2012) variation in surface energy flux and its forcing parameters over different agro-climatic regions (ACRs) of India. Energy fluxes were retrieved using a single-source surface energy balance model (here vegetation and soil is considered as a single unit). Energy flux observations over different ACRs allowed comparison of the seasonal transition of latent heat flux (LE), net radiation (R_n), soil heat flux (G), available energy (Q = R_n – G), and evaporative fraction (EF) as terrestrial links to the atmosphere. The seasonal and inter-annual variation in EF was investigated by plotting against the soil moisture information retrieved from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) global monthly data product (1° × 1° spatial resolution). Decadal and seasonal analysis showed that energy fluxes vary widely in time and space due to variability in surface radiation parameters (T_s, α), vegetation cover, soil moisture, and air temperature (T_a), which influence the seasonal transition of monsoon through LE and EF. Among the ACRs, LE and EF were found lowest in the Western Dry Region (WDR) and highest in the Western Himalayan Region (WHR). The spatiotemporal depiction of MODIS LE and MODIS EF over a span of 10 years can identify the hotspots and monsoon intensity over different ACRs. Climatic parameters that are susceptible to changes resulting from climate change are thoroughly studied in the present analysis.     

Evaluation of the Geostationary Ocean Color Imager (GOCI) to monitor the dynamic characteristics of suspension sediment in Taihu Lake

To accurately observe the dynamic concentration of total suspended matter (C_TSM) by geostationary satellite, Geostationary Ocean Color Imager (GOCI), a new, regionally empirical combination algorithm, was developed based on the in situ measurement of water properties. Also, the ability of GOCI (with a 1 h temporal resolution) to capture dynamic change in C_TSM was evaluated using in situ buoy-measured data. The validation results indicate that the combination algorithm (combination of two- and three-band ratio algorithms) can achieve acceptable retrieval results for C_TSM, with 34.52% root mean square error percentage (RMSP) for validation data and 45.01% RMSP for GOCI match-up points. The depth of reflectance valley at 680 nm (R_rs-depth,680) is considered as an index for deciding whether to utilize a two- (R_rs-depth,680 ≤ 0.005) or three-band (R_rs-depth,680 > 0.005) algorithm in the combination algorithm. This combination algorithm overcomes some shortcomings of two- and three-band ratio algorithms of C_TSM in turbid productive water. The results show that sediment resuspension will significantly change the optical properties of water and decrease the universality of the C_TSM retrieval algorithm in the presence of a large area of algae. The influence of sediment resuspension on the C_TSM retrieval algorithm is significant in the central lake but less so in the other four lakes studied due to lake morphology and algal biomass.     

Relationships between vegetation indices,fractional cover retrievals and the structure and composition of Brazilian Cerrado natural vegetation

This study explores the use of the relationship between the normalized difference vegetation index (NDVI) and the shortwave infrared ratio (SWIR32) vegetation indices (VI) to retrieve fractional cover over the structurally complex natural vegetation of the Cerrado of Brazil using a time series of imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS). Data from the EO-1 Hyperion sensor with 30 m pixel resolution is used to sample geographic and seasonal variation in NDVI, SWIR32, and the hyperspectral cellulose absorption index (CAI), and to derive end-member values for photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and bare soil (BS) from a suite of protected and/or natural vegetation sites across the Cerrado. The end-members derived from relatively pure 30 m pixels are then applied to a 500 m pixel resolution MODIS time series using linear spectral unmixing to retrieve PV, NPV, and BS fractional cover (F_PV, F_NPV, and F_BS). The two-way interaction response of MODIS-equivalent NDVI and SWIR32 was examined for regions of interest (ROI) collected within protected areas and nearby converted lands. The MODIS NDVI, SWIR32 and retrieved F_PV, F_NPV, and F_BS are then compared to detailed cover and structural composition data from field sites, and the influence of the structural and compositional variation on the VIs and cover fractions is explored. The hyperion ROI analysis indicated that the two-way NDVI–SWIR32 response behaved as an effective surrogate for the two-way NDVI–CAI response for the campo limpo/grazed pasture to cerrado sensu stricto woody gradient. The SWIR32 sensitivity to the NPV and BS variation increased as the dry season progressed, but Cerrado savannah exhibited limited dynamic range in the NDVI–CAI and NDVI–SWIR32 two-way responses compared to the entire landscape, which also comprises fallow croplands and forests. Validation analysis of MODIS retrievals with Quickbird-2 images produced an RMSE value of 0.13 for F_PV. However, the RMSE values of 0.16 and 0.18 for F_BS and F_NPV, respectively, were large relative to the seasonal and inter-annual variation. Analysis of site composition and structural data in relation to the MODIS-derived NDVI, SWIR32 and F_PV, F_NPV, and F_BS, indicated that the VI signal and derived cover fractions were influenced by a complex mix of structure and cover but included a strong year-to-year seasonal effect. Therefore, although the MODIS NDVI–SWIR32 response could be used to retrieve cover fractions across all Cerrado land covers including bare cropland, pastures and forests, sensitivity may be limited within the natural Cerrado due to sub-pixel heterogeneity and limited BS and NPV sensitivity.     

A Penman-Monteith evapotranspiration model with bulk surface conductance derived from remotely sensed spatial contextual information

ABSTRACT

A novel approach involving the use of the contextual information in a scatter plot of Moderate Resolution Imaging Spectrometer (MODIS) derived Land Surface Temperature versus Fraction of Vegetation (LST vs. F_v) has been proposed in this study to obtain pixel-wise values of bulk surface conductance (G_s) for use in the Penman-Monteith (PM) model for latent heat flux (λ_ET) estimation. Using a general expression for G_s derived by assuming a two-source total λ_ET (canopy transpiration plus soil evaporation) approach proposed by previous researchers, minimum and maximum values of G_s for a given region can be inferred from a trapezoidal scatter plot of pixel-wise values of LST and corresponding F_v. Using these as limiting values, G_s values for each pixel can be derived through interpolation and subsequently used with the PM model to estimate λ_ET for each pixel. The proposed methodology was implemented in 5 km × 5 km areas surrounding each of four flux towers located in tropical south-east Asia. Using climate data from the tower and derived G_s values the PM model was used to obtain pixel-wise instantaneous λ_ET values on six selected dates/times at each tower. Excellent comparisons were obtained between tower measured λ_ET and those estimated by the proposed approach for all four flux tower locations (R² = 0.85–0.96; RMSE = 18.27–33.79 W m^–2). Since the LST- F_v trapezoidal method is simple, calibration-free and easy to implement, the proposed methodology has the potential to provide accurate estimates of regional evapotranspiration with minimal data inputs.